Control apparatus, control method, and storage medium

ABSTRACT

A control apparatus and method that captures video image includes acquiring a parameter for recognition processing with respect to acquired image data and changing the acquired parameter according to a change in zoom magnification of an image capturing unit.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of co-pending U.S. patent applicationSer. No. 14/605,723, filed Jan. 26, 2015, which claims foreign prioritybenefit of Japanese Patent Application No. 2014-012800 filed Jan. 27,2014, both which are hereby incorporated by reference herein in theirentirety.

BACKGROUND Field

Aspects of the present invention generally relate to a controlapparatus, a control method for the control apparatus, and a storagemedium.

Description of the Related Art

In monitoring systems and monitoring camera systems, there aretechniques for detecting a moving object in a video image by using videoimage recognition processing. Moreover, there is a recognition techniquefor constantly capturing a detected moving object. Such a technique isknown as a moving object tracking technique.

In addition, Japanese Patent Application Laid-Open No. 2012-242970discusses video recognition by which an object having a size larger thana predetermined minimum detection size is detected. However, when zoommagnification is changed, there is a possibility that the video imagerecognition processing may not be performed appropriately.

For example, a zoom magnification may be changed after a maximum sizeand a minimum size of an object to be detected by recognition processingare set. In such a case, due to a change in the zoom magnification, anobject that could be detected if the zoom magnification remains the samemay not be detected. Moreover, for example, a zoom magnification may bechanged after a maximum size and a minimum size of an object are set. Insuch a case, due to a change in the zoom magnification, an object thatcould not be detected if the zoom magnification remains the same may bedetected.

SUMMARY

According to an aspect of the present invention, a control apparatusincludes an acquisition unit configured to acquire a parameter forrecognition processing with respect to image data acquired by imagecapturing by an image capturing unit, and a control unit configured tochange the parameter acquired by the acquisition unit according to achange in zoom magnification of the image capturing unit.

Further features of the present disclosure will become apparent from thefollowing description of exemplary embodiments with reference to theattached drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating a configuration of a video imageprocessing system.

FIG. 2 is a block diagram illustrating a configuration example of acontrol apparatus.

FIG. 3 is a diagram illustrating a structure example of informationmanaged by a locus management unit.

FIGS. 4A and 4B are diagrams illustrating examples of associationbetween an object and a human body.

FIGS. 5A, 5B, and 5C are diagrams illustrating examples of screens usedwhen a human body detection size is set.

FIGS. 6A and 6B are diagrams illustrating structure examples ofparameters for video image recognition processing.

FIG. 7 is a flowchart illustrating processing performed by a controlapparatus.

FIG. 8 is a flowchart illustrating processing performed by a parametercontrol unit.

DESCRIPTION OF THE EMBODIMENTS

Various exemplary embodiments will be described in detail below withreference to the drawings. Configurations described in exemplaryembodiments below are merely examples and are not seen to be limited tothe following configurations.

FIG. 1 is a diagram illustrating a configuration of a video imageprocessing system. The video image processing system includes cameras101 and 108, a network 102 such as a local area network (LAN), personalcomputers (PCs) 104 and 106, and displays 105 and 107. Each of thecameras 101 and 108 includes an optical zoom mechanism. The displays 105and 107 display images based on image data from the cameras 101 and 108,and processing results of the PCs 104 and 106. Moreover, each of thedisplays 105 and 107 can provide a user interface used when a setting ofvideo image recognition processing according to the present disclosureis made.

A configuration example of a control apparatus 200 of a first exemplaryembodiment is described with reference to FIG. 2. In the description ofthe present exemplary embodiment, the control apparatus 200 is installedin a camera (e.g., the camera 101 or the camera 108 illustrated in FIG.1). However, a function of the control apparatus 200 may be performedby, for example, a PC (corresponding to the PC 104 or the PC 106illustrated in FIG. 1), or an image processing circuit mounted inside acamera capable of capturing moving images. Alternatively, a function ofthe control apparatus 200 may be performed by other devices. The controlapparatus 200 has a function of not only displaying a setting screen forsetting a parameter of video image recognition processing (e.g., humanbody detection) on a display screen of a display device 210, but alsosetting a parameter corresponding to an instruction from a user withrespect to the parameter setting screen. In the present exemplaryembodiment, the display device 210 illustrated in FIG. 2 corresponds tothe displays 105 or 107.

The control apparatus 200 includes an image acquisition unit 201, anobject detection unit 202, an object tracking unit 203, a human bodydetection unit 204, a parameter setting unit 205, an object associationunit 206, a locus management unit 207, a locus information determinationunit 208, and an external output unit 209. Moreover, the controlapparatus 200 includes a zoom control unit 211 that controls the zoommechanism of the camera, and a parameter control unit 212 that controlsa parameter according to a zoom magnification (a zoom value). Thecontrol apparatus 200 is connected to the display device 210 including,for example, a cathode ray tube (CRT) and a liquid crystal display. Thedisplay device 210 displays a processing result of the control apparatus200 by using images and characters. Hereinafter, a description is mainlygiven of a case where a moving image is displayed on a display screen ofthe display device 210.

The image acquisition unit 201 acquires a moving image or a still imagesupplied from an internal imaging sensor or an external unit, andtransmits the acquired moving image or still image to the objectdetection unit 202.

Upon acquisition of the moving image, the image acquisition unit 201sequentially transmits each of frame images forming the moving image tothe object detection unit 202. On the other hand, upon acquisition ofthe still image, the image acquisition unit 201 transmits the acquiredstill image to the object detection unit 202. The supply source of themoving image or the still image is not limited to the internal imagingsensor or the external unit. For example, the moving image or the stillimage may be supplied from a server apparatus or an image capturingapparatus in a wired or wireless manner. Alternatively, the moving imageor the still image may be acquired from a memory inside the controlapparatus 200 instead of the external unit. In the description below,the object detection unit 202 receives one image regardless of whetherthe image acquisition unit 201 has acquired a moving image or a stillimage. If the image acquisition unit 201 acquires the moving image, theobject detection unit 202 receives one image that corresponds to eachframe of the moving image. On the other hand, if the image acquisitionunit 201 acquires the still image, the object detection unit 202receives one image that corresponds to the still image.

The object detection unit 202 uses a background subtraction technique todetect an object from the frame image acquired from the imageacquisition unit 201. That is, the object detection unit 202 comparesthe frame image acquired by the image acquisition unit 201 and apredetermined frame image (a background image) to detect the object.Subsequently, the object detection unit 202 generates object informationaccording to the detected object. The object information includesinformation about a position of the object on the screen, acircumscribed rectangle, and an object size. Although the objectdetection unit 202 has the function of detecting the object from theimage by using the background subtraction technique, the detectiontechnique is not limited thereto.

The object tracking unit 203 associates objects detected from aplurality of respective frame images with each other, based on theobject information corresponding to the plurality of frame images. Forexample, the object detection unit 202 may detect, from an image in atarget frame, an object corresponding to an object detected from animage in the immediate preceding frame of the target frame. In such acase, the object tracking unit 203 associates these objects in therespective frames with each other.

For example, the object tracking unit 203 assigns “object identification(ID)=A” to the object detected by the object detection unit 202 from theimage in the immediate preceding frame of the target frame. If theobject detection unit 202 detects an object corresponding to the objecthaving “object ID=A” from the image in the target frame, the objecttracking unit 203 assigns “object ID=A” to this object as well.Accordingly, if the object corresponding to each of the plurality offrames is detected, the object tracking unit 203 assigns the same objectID to each of such objects. The object tracking unit 203 assigns a newobject ID to an object newly detected in the target frame.

The object tracking unit 203 can use a following method for determiningwhether objects in different frames correspond to each other. Accordingto the determination method, if a predicted movement position of anobject identified by using a movement vector of a detected object and aposition of the detected object are provided within a certain distance,the object tracking unit 203 determines that these objects aresubstantially the same. That is, the object tracking unit 203 identifiesa distance between a position of an object detected from a frame imageand a position of an object identified based on movement vectorinformation about the frame image. If the identified distance is lessthan a threshold value, the object tracking unit 203 associates thisobject with the object in the other frame image.

However, the object association method is not limited thereto. Forexample, the object tracking unit 203 may use color, shape, and size(area) of an object to associate one object with another. In such acase, objects having a high correlation between frames are associated.Moreover, a combination of movement vector information and informationsuch as color, shape, and size of an object may be used for objectassociation. The object tracking unit 203 associates the objectsdetected in the plurality of frames with each other according to apredetermined condition, and tracks the associated objects. For example,in a case where the same person is detected in a plurality of frames,the object tracking unit 203 assigns the same object ID to the person.The object association method is not limited to a specific method.Various methods that perform processing similar to the above may beused.

The human body detection unit 204 executes human body detectionprocessing with respect to a region in which the object detection unit202 has detected an object, from among object detection regions set bythe parameter setting unit 205, thereby detecting a human body. Thehuman body detection unit 204 of the present exemplary embodimentexecutes the human body detection processing with respect to a region (ahuman body detection region) including a region in which the object isdetected and the vicinity thereof. For example, the human body detectionunit 204 may detect an object having a width and height of 20 pixels by100 pixels around coordinates (X, Y) within a frame. In such a case, thehuman body detection unit 204 performs the human body detectionprocessing with respect to a region having a width and height of 30pixels and 150 pixels around the coordinates (X, Y) of the frame.

Moreover, the human body detection unit 204 refers to maximum andminimum sizes for human body detection set by the parameter setting unit205. Accordingly, the human body detection unit 204 can omit the humanbody detection processing outside the range of the maximum size and theminimum size. That is, in the human body detection region identified bydetection of the object, the human body detection unit 204 can omit thehuman body detection processing if the human body detection region islarger than the maximum size. The human body detection unit 204 can alsoomit the human body detection processing if the human body detectionregion is smaller than the minimum size. However, the human bodydetection unit 204 may perform the human body detection processingwithout carrying out such omission, and then a detection result of ahuman body that is larger than the maximum size and a detection resultof a human body that is smaller than the minimum size can be excludedfrom processing results of the human body detection processing.

The human body detection unit 204 compares a pattern image of a humanbody and a frame image to detect the human body from the frame image.However, the human body detection method is not limited thereto.Besides, in the present exemplary embodiment, a detection target is ahuman body. However, the detection target is not limited thereto.Alternatively, a detection target may be a face of a person, a bicycle,and an animal. Moreover, the human body detection unit 204 cansimultaneously execute a plurality of types of detection processing suchthat a plurality of types of specific objects is detected. That is, thehuman body detection unit 204 of the present exemplary embodiment candetect not only a human body, but also various predetermined objectsfrom image data by using recognition processing.

Moreover, the human body detection region may not necessarily bedetermined based on the region in which the object detection unit 202has detected the object. For example, the human body detection unit 204may identify a human body detection region from a parameter set by theparameter setting unit 205, thereby performing human body detectionprocessing. In such a case, the object detection unit 202 may omitobject detection processing.

The parameter setting unit 205 sets, for example, a parameter regardinga detection processing range (a human body detection region) of thehuman body detection processing in each frame, and a parameter regardingmaximum and minimum sizes for human body detection.

In addition to the setting of the human body detection, the parametersetting unit 205 may similarly set a parameter regarding detectionprocessing to be performed by the object detection unit 202. Forexample, the parameter setting unit 205 can set parameters regarding anobject detection region and maximum and minimum sizes for objectdetection as parameters for the object detection unit 202. However, inthe present exemplary embodiment, the object detection region is anentire image acquired by the image acquisition unit 201. Generally, thesmaller the object detection region, the higher the processing speed.

The object association unit 206 associates the object detected by theobject detection unit 202 with the human body detected by the human bodydetection unit 204. An example of such association of the object withthe human body is described with reference to FIGS. 4A and 4B. FIG. 4Aillustrates an example case in which a circumscribed rectangle 401 ofthe object detected by the object detection unit 202 does not include acircumscribed rectangle 402 of the human body detected by the human bodydetection unit 204. The object detection unit 202 of the presentexemplary embodiment performs the object detection processing withrespect to the entire frame. The human body detection unit 204 performsthe human body detection processing with respect to a region serving asthe human body detection region, including a vicinity of thecircumscribed rectangle of the object detected by the object detectionunit 202.

When the object and the human body are detected as illustrated in FIG.4A, the object association unit 206 associates the object with the humanbody if an overlap ratio exceeds a threshold value that is setbeforehand. The overlap ratio is a ratio of the circumscribed rectangle402 of the human body to the circumscribed rectangle 401 of the object.That is, if the ratio of an overlap area in which the circumscribedrectangle 401 of the object overlaps with the circumscribed rectangle402 of the human body, to an area of the circumscribed rectangle 402 ofthe human body exceeds the threshold value, the object association unit206 associates the object corresponding to the circumscribed rectangle401 with the human body corresponding to the circumscribed rectangle402.

On the other hand, FIG. 4B illustrates an example case in which aplurality of human bodies is detected from a circumscribed rectangle 403of a detected object. In such a case, if a ratio of an overlap area inwhich the object circumscribed rectangle 403 overlaps with acircumscribed rectangle 404 of a human body, to an area of thecircumscribed rectangle 404 exceeds a threshold value, the objectassociation unit 206 associates the object corresponding to thecircumscribed rectangle 403 with the human body corresponding to thecircumscribed rectangle 404. Moreover, if a ratio of an overlap area inwhich the object circumscribed rectangle 403 overlaps with acircumscribed rectangle 405 of a human body, to an area of thecircumscribed rectangle 405 exceeds a threshold value, the objectassociation unit 206 associates the object corresponding to thecircumscribed rectangle 403 with the human body corresponding to thecircumscribed rectangle 405. There are cases where the objectassociation unit 206 associates one object with a plurality of humanbodies. The association of the object with the human body is not limitedto the above-described method.

The locus management unit 207 acquires information about objects fromthe object detection unit 202, the object tracking unit 203, and theobject association unit 206 to manage the acquired information asmanagement information for each object. An example of managementinformation 301 managed by the locus management unit 207 is describedwith reference to FIG. 3. The locus management unit 207 of the presentexemplary embodiment manages object information 302 for each object IDas illustrated in FIG. 3. The object information 302 corresponding toone object ID includes a time stamp indicating a date and time when theobject information is generated. The object information 302 alsoincludes information 303 of each frame in which the object is detected.The information 303 includes a time stamp when the information isgenerated, a coordinate position (Position) of the detected object,information (Bounding box) indicating a circumscribed rectangleincluding a region of the detected object, a size of the object, and anattribute of the object. However, information to be included in theinformation 303 is not limited to those pieces of information. Theinformation 303 may include other information. The locus informationdetermination unit 208 uses such management information 301 managed bythe locus management unit 207.

The locus management unit 207 updates the attribute (Attribute) of theobject according to a result of the association by the objectassociation unit 206. Moreover, the locus management unit 207 may updatean attribute (Attribute) of a past object according to the associationresult. The locus management unit 207 may update an attribute(Attribute) of a subsequent object according to the association result.With such processing, tracking results of the objects having the sameobject ID can have the same attribute at any time.

The locus information determination unit 208 functions as a passingobject detection unit. The locus information determination unit 208performs processing for determining whether the object has passedthrough a detection line according to the parameter set by the parametersetting unit 205 and the management information managed by the locusmanagement unit 207. The detection line can be set by a user. Forexample, the user can operate a user interface on a parameter settingscreen of the display device 210 to set the detection line. Theparameter setting unit 205 of the present exemplary embodiment, forexample, can set information for identifying a line segment set by theuser as a parameter in the locus information determination unit 208.

The locus information determination unit 208 determines whether amovement vector intersects the line segment for passage detection, themovement vector indicating a movement from a circumscribed rectangle ofa human body attribute object in the immediate preceding frame of atarget frame to a circumscribed rectangle of a human body attributeobject in the target frame. In the present exemplary embodiment, a humanbody attribute object represents an object associated with the humanbody by the object association unit 206. Moreover, such intersectiondetermination corresponds to determination whether the human bodyattribute object has passed the line segment for passage detection. Aresult of determination made by the locus information determination unit208 may be output to an external unit (e.g., the display device 210) viathe external output unit 209. Moreover, the external output unit 209 mayhave a function of a display unit including CRT or a liquid crystalscreen. In such a case, the determination result can be displayed byusing the external output unit 209 instead of the display device 210.

The present exemplary embodiment has been described using the examplecase in which the locus information determination unit 208 detects thatthe human body attribute object has passed a predetermined line segment.However, the present exemplary embodiment is not limited to such anexample case. For example, in a case where a predetermined region is setas a parameter, the locus information determination unit 208 may detectthat the human body attribute object has intruded into the region.Moreover, the locus information determination unit 208 may detect thatan animal object has intruded into the region instead of the human bodyattribute object. In addition, the locus information determination unit208 may execute various detection processing using locus information anda parameter of event detection.

Next, video image recognition processing according to the firstexemplary embodiment is described with reference to FIGS. 5A, 5B, 5C, 6Aand 6B.

FIGS. 5A through 5C are diagrams illustrating a setting of human bodydetection size. A parameter setting screen illustrated in each of FIGS.5A through 5C is displayed on the display device 210, for example.

FIG. 5A illustrates an example of a screen on which a maximum size and aminimum size for human body detection are set.

In FIG. 5A, a setting screen 500 serves as a screen on which a parameterof human body detection is set. On the screen 500 illustrated FIG. 5A, astreet, a human body 501, and a human body 502 are shown. The streetextends from the upper left to the lower right of the screen 500. Thehuman body 501 is shown in the upper left (far), whereas the human body502 is shown in the lower right (near). A setting rectangle 503 servesas a user interface (UI) used to set a maximum size for human bodydetection. Similarly, a setting rectangle 504 serves as a UI used to seta minimum size for human body detection.

The human body detection unit 204 of the present exemplary embodimentcompares a pattern image of a human body with a frame image to detect ahuman body from the frame image. In particular, the human body detectionunit 204 rescales the frame image according to sizes of the settingrectangles 503 and 504. Then, the human body detection unit 204 comparesthe rescaled frame image with the pattern image of the human body todetect a human figure. For example, the human body detection unit 204generates frame images that are respectively rescaled to one-half,one-third, and one-fourth according to the sizes of the settingrectangles 503 and 504. Subsequently, the human body detection unit 204compares each of the generated images with the pattern image of thehuman body, thereby detecting a human body.

In such a case, when the user performs an operation to reduce a zoommagnification, the human body detection unit 204 controls themagnification of the frame image such that the human figure detectedbefore reduction in the zoom magnification is detected even after thezoom magnification is changed. Particularly, the human body detectionunit 204 generates, for example, frame images that are respectivelyrescaled to one-third, one-fourth, and one-sixth. Subsequently, thehuman body detection unit 204 compares each of the generated images withthe pattern image of the human body, thereby detecting the human body.

The detection method for human body is not limited to theabove-described method. For example, the human body detection unit 204may rescale a pattern image of a human body according to sizes of thesetting rectangles 503 and 504, so that the rescaled pattern image ofthe human body and a frame image may be compared to detect a human body.

Accordingly, the human body detection processing is performed such thatonly a human body within a set range of the human body detection size isdetected. This can enhance speed or accuracy of the processing. Thesizes of the setting rectangles 503 and 504 can be changed by a mouseoperation performed by an operator. The mouse operation includesdragging a border or a node of the setting rectangles 503 and 504. Thediagram illustrated in FIG. 5A has been described using the example casein which the maximum size and the minimum size for human body detectionare set. However, only a maximum size or a minimum size may be set.

FIG. 5B is a display example of a screen on which one region of thescreen illustrated in FIG. 5A is zoomed in. A rectangular zoom range 505illustrated in FIG. 5A corresponds to the screen illustrated in FIG. 5B.Thus, when the zoom range 505 illustrated in FIG. 5A is zoomed in, ascreen 510 illustrated in FIG. 5B is obtained. In FIG. 5B, the zoomrange 505 illustrated in FIG. 5A is magnified 2.5 times.

FIGS. 6A and 6B are diagrams illustrating structure examples of settingparameters set by the parameter setting unit 205. The control apparatus200 can display parameter display screens illustrated in FIGS. 6A and 6Bon the display device 210, for example.

FIG. 6A is a diagram illustrating setting values of the settingrectangles 503 and 504.

In FIG. 6A, a maximum size (Max Size) for human body detection is set toa width and height of (900, 900) pixels, whereas a minimum size (MinSize) is set to a width and height of (250, 250) pixels. The screen 500has a resolution of (1280, 1024) in width and height. Herein, zoommagnification is same size magnification.

Herein, assume that the setting values illustrated in FIG. 6A areapplied as they are, to a zoomed screen as illustrated in FIG. 5B.

As shown on the screen 510 in FIG. 5B, the use of a zoom-in operationenlarges an image of the human body to be captured. After the zoom-inoperation, it is conceivable that the image of the human body in a sizethat is larger than that of the setting rectangle 503 (Max size in FIG.6A) may be captured. However, in a case where the maximum size (900,900) for human body detection is applied as is, there is a possibilitythat a large human body may not be detected.

Moreover, for example, an object that has a size smaller than theminimum size for human body detection before being zoomed in should notundergo the human body detection processing. However, such an object maybecome a target object for the human body detection processing afterbeing zoomed in. In such a case, the human body detection processingthat is not intended by the user may be performed, causing an increasein a processing load.

Such a problem may also occur when the object is zoomed out. That is,when the use of the zoom-out operation reduces a size of the human bodywithin a frame, the parameter of the minimum size for human bodydetection may not be changed before and after the zoom-out operation. Insuch a case, there is a possibility that a human body may not bedetected. In addition, the maximum size for human body detection may notbe changed before and after the zoom-out operation. In such a case, thehuman body detection processing needs to be performed with respect to ahuman body that did not have a detection target size before being zoomedout, causing consumption of unnecessary processing time.

The parameter control unit 212 of the present exemplary embodimentchanges a parameter to be used in video image recognition processingaccording to a change in zoom magnification. The parameter is, forexample, a maximum size and a minimum size for human body detection.With the change in the parameter, the parameter control unit 212 enablessuitable recognition processing to be performed even after the zoommagnification is changed. As described above, the human body detectionunit 204 of the present exemplary embodiment compares a pattern image ofthe human body with a plurality of rescaled frame images, therebydetecting the human body. In this example, a scale factor used torescale the frame image is changed according to a change in the zoommagnification. That is, the parameter control unit 212 changes themaximum size and the minimum size of the frame image to be used forhuman body detection according to a change in the zoom magnification.

Moreover, the human body detection unit 204 rescales the pattern imageof the human body, and compares the rescaled pattern image and the frameimage to detect the human body. When the human body detection unit 204performs such human body detection, a scale factor used to rescale thepattern image of the human body is changed according to a change in thezoom magnification. That is, the parameter control unit 212 changes themaximum size and the minimum size of the pattern image to be used forhuman body detection according to a change in the zoom magnification.

FIG. 5C is an example of a screen displayed when the screen 500illustrated in FIG. 5A is zoomed in and the setting value illustrated inFIG. 6A is changed according to the zoom magnification. The parametersillustrated in FIG. 6A are changed to parameters illustrated in FIG. 6Bby the processing which will be described below. The human bodydetection unit 204 executes the human body detection processing based onthe changed parameters.

When the screen 500 illustrated in FIG. 5A is zoomed to a screen 520illustrated in FIG. 5C, a zoom magnification changes from same size to2.5 times. The parameter control unit 212 of the present exemplaryembodiment changes the maximum size and the minimum size for human bodydetection according to such a change in the zoom magnification. Theparameter control unit 212 changes the minimum size for human bodydetection to a size (625, 625) illustrated in FIG. 6B, which is 2.5times as large as that (250, 250) illustrated in FIG. 6A. Thus, theminimum size illustrated in FIG. 6B is applied after the zoommagnification is changed. Similarly, the maximum size for human bodydetection should be changed to a size that is 2.5 times as large as thatillustrated in FIG. 6A. However, since such a size exceeds a screenrange, the parameter control unit 212 of the present exemplaryembodiment changes the maximum size to a size (1024, 1024) in which aheight of the screen 520 is an upper limit.

The parameter control unit 212 of the present exemplary embodimentexecutes such parameter change processing each time zoom magnificationinformation is received from the zoom control unit 211. Moreover, eachtime the parameter is changed, the parameter control unit 212 notifies aparameter setting tool side of the changed parameter. This enables a UIto be dynamically changed according to a change in the zoommagnification.

FIG. 5C is a diagram illustrating a UI of the parameter setting tool,the UI being displayed after the maximum size and the minimum size forhuman body detection processing are changed according to a change in thezoom magnification. A rectangle 522 illustrated in FIG. 5C correspondsto the setting rectangle 503 illustrated in FIG. 5A, whereas a rectangle521 illustrated in FIG. 5C corresponds to the setting rectangle 504illustrated in FIG. 5A.

As described above, when a zoom control that steps up a zoommagnification is performed after the maximum size or the minimum sizefor human body detection is designated, the parameter control unit 212of the present exemplary embodiment controls the maximum size and theminimum size to be larger than those prior to the zoom control.Moreover, when a zoom control that reduces a zoom magnification isperformed after the maximum size or the minimum size for human bodydetection is designated, the parameter control unit 212 controls themaximum size and the minimum size to be smaller than those prior to thezoom control.

Alternatively, when changing the parameter according to a change in thezoom magnification, the parameter control unit 212 may display a messageabout the change in the parameter on a screen. Alternatively, beforechanging the parameter, the parameter control unit 212 may display aparameter change notification on the screen, so that the parametercontrol unit 212 may change the parameter after receiving approval fromthe user.

Moreover, in the present exemplary embodiment, the parameters relatingto the maximum size and the minimum size for human body detection arechanged according to the zoom magnification. However, in a case wherethe changed size exceeds a predetermined threshold value, the human bodydetection processing may be stopped or canceled. Alternatively, amessage such as a warning message may be displayed instead of stoppingor cancelling the human body detection processing. Therefore, forexample, an error in the parameter of the recognition processing can beprevented.

The present exemplary embodiment has been described using the examplecase in which a human body detection size is set by using a rectangle.However, other shapes such as a polygon and a circle may be used.

Moreover, in the present exemplary embodiment, the parameters changed bythe parameter control unit 212 serve as the maximum size and the minimumsize for human body detection. However, other parameters that aredependent on a captured image size or a location on an image may beused. In the above description, for example, if a distance between aposition of an object detected from a frame image and a position of anobject identified by a movement vector relating to the frame image isless than a threshold value, the object tracking unit 203 associates theobject with an object of another frame. However, this threshold valuemay be a parameter that changes according to a change in zoommagnification.

Moreover, for example, a parameter (a region or a line segment forpassage detection) used for event detection by the locus informationdetermination unit 208 may be changed according to a change in zoommagnification. More particularly, the parameter control unit 212 canchange a position or a length of a line segment used for the passagedetection and a position or a size of a region used for intrusiondetection, according to a change in zoom magnification.

Moreover, for example, an object detection range may be used as aparameter that changes according to a change in zoom magnification. Inthe present exemplary embodiment, the object detection range has beendescribed as an entire screen.

Moreover, in the above description, for example, if an overlap ratioexceeds a threshold value, the object association unit 206 associates anobject with a human body. The overlap ratio represents a ratio of anoverlap area in which a circumscribed rectangle of the object overlapswith a circumscribed rectangle of the human body, to an area of thecircumscribed rectangle of the human body. The threshold value in such acase may be set as a parameter that changes according to a change inzoom magnification. Since a ratio such as the overlap ratio compares theareas, the ratio is not converted by the same magnification based on thezoom magnification as the human body detection size according to thepresent exemplary embodiment. The parameter control unit 212 of thepresent exemplary embodiment uses a table in which the zoommagnification and the overlap ratio are associated, thereby changing aparameter that is not converted by the same magnification.

The present exemplary embodiment has been described using the examplecase in which a parameter is relatively converted according to a changein zoom magnification by using a maximum size or a minimum size forhuman body detection designated via a user interface, as a referencevalue. That is, in the above description, for example, if the zoommagnification is doubled after the maximum size (the reference size) forhuman body detection is set by using the user interface, the maximumsize for human body detection is increased to a value twice as large asthe reference value. However, the present exemplary embodiment is notlimited thereto.

For example, assume that an absolute range three-dimensional region andan absolute size range can be acquired. In the absolute rangethree-dimensional region, a camera position and a position in which adetection target object (herein, a human body) can be present areidentified. The absolute size range is a range that the detection targetobject can take within the absolute range three-dimensional region. Theacquisition of the absolute range three-dimensional region and theabsolute size range enables the parameter control unit 212 to identifyan appropriate parameter (herein, a maximum size and a minimum size forhuman body detection) with respect to a zoom value. Moreover, by usingthe zoom value when the parameter is determined, as a reference value,the parameter control unit 212 can change a recognition parameteraccording to subsequent changes in zoom magnification.

Moreover, in FIGS. 5A, 5B, and 5C, an angle of the camera is set suchthat a lower limit of the object size is finite. That is, the presentexemplary embodiment has been described using the example case in whicha camera position, a depression angle, and a detection target object areprovided such that the upper limit and the lower limit of size of ahuman body to be captured on a video image are finite. However, forexample, in a case where an object is positioned at infinity, it istheoretically conceivable that the maximum size and the minimum size maynot be set depending on a camera position, a direction in which thecamera is facing, and a type of the object to be detected. In such acase, an object detection parameter according to a change in a zoomvalue (a zoom magnification) should not be changed, or a minimum sizemay be intentionally set. Alternatively, a camera installation locationor a camera installation direction may be changed. The control apparatus200 of the present exemplary embodiment can select, based on anoperation by the user, whether to change the parameter according to achange in the zoom magnification.

In the present exemplary embodiment, the optical zoom is used as thezoom mechanism of the camera. However, a digital zoom may be used.Hereinafter, a description is given for processing performed when thedigital zoom is employed as the zoom mechanism of the camera.

When the digital zooming is carried out, a zoom range 505 on the screen500 is displayed as shown in the screen 510. In such a case, theparameter control unit 212 changes the setting rectangles 503 and 504according to a digital zoom magnification similar to the optical zoom.For example, if the zoom magnification is changed from same size to 2times by the digital zoom, the parameter control unit 212 changes andenlarges a maximum size and a minimum size for object detection by 2times. Subsequently, the parameter control unit 212 notifies the displaydevice 210 of the changed parameter. Thus, a display of the userinterface can be changed as illustrated in FIG. 5C. Accordingly, thedigital zoom operation and the user interface are linked, so that theuser can recognize that the parameter has been changed according to achange in the zoom magnification. However, in the digital zoomoperation, there are cases where an image actually processed by thehuman body detection unit 204 is a captured image before being zoomed,instead of a digitally zoomed image. In such a case, the parametershould not be changed according to a change in the zoom magnification.That is, the parameter control unit 212 determines whether an imageregion serving as a target of video image recognition processing hasbeen changed before and after a change in the zoom magnification. If theimage region has not been changed, the parameter control unit 212 doesnot change the parameter of the recognition processing according to thechange in the zoom magnification.

Hereinafter, a case is described in which an image to be processed bythe human body detection unit 204 is an image which is clipped afterbeing digitally zoomed. If a maximum size for human body detectionexceeds the clipped-image range, the parameter control unit 212 maychange a parameter such that the maximum size for human body detectionis reduced to the clipped-image range. For example, in a case where themaximum size for human body detection before the digital zoom operationis (1000, 1000) and a size of the image to be clipped by the digitalzoom operation is (800, 800), the parameter control unit 212 may changethe maximum size to (800, 800). Alternatively, if the minimum size forhuman body detection exceeds the clipped-image range, the parametercontrol unit 212 may stop or cancel the human body detection processing.

Next, operations of the control apparatus 200 according to the firstexemplary embodiment are described with reference to a flowchartillustrated in FIG. 7. The control apparatus 200 of the presentexemplary embodiment executes the processing illustrated in FIG. 7 bycausing a central processing unit (CPU) serving as a control unit toread a control program for the processing illustrated in FIG. 7 from amemory and to execute the read program. Further, since the controlapparatus 200 of the present exemplary embodiment is installed in thecamera, the processing illustrated in FIG. 7 starts when the camera isactivated. Alternatively, the control apparatus 200 may be anotherapparatus independent from the camera. The control apparatus 200 may bemounted on a device, such as a PC and a mobile terminal, which displaysan image captured by the camera. In step S701, the control unit (notillustrated) of the control apparatus 200 determines whether theprocessing illustrated in FIG. 7 should be continued. For example, whena user gives an instruction that the processing illustrated in FIG. 7should be finished, the control unit determines that the processingillustrated in FIG. 7 needs to be finished. When such an instruction isnot provided from the user, the control unit determines that theprocessing illustrated in FIG. 7 should be continued. Accordingly, ifthe control unit determines that the processing should be continued (YESin step S701), the operation proceeds to step S702. On the other hand,if the control unit determines that the processing should not becontinued (NO in step S701), the processing ends.

In step S702, the image acquisition unit 201 acquires image data inputto the control apparatus 200. In step S703, the object detection unit202 performs object detection processing with respect to the imageacquired by the image acquisition unit 201. In step S704, the objectdetection unit 202 determines whether an object is detected in stepS703. If the object detection unit 202 determines that the object isdetected (YES in step S704), the operation proceeds to step S705. On theother hand, if the object detection unit 202 determines that the objectis not detected (NO in step S704), the operation returns to step S701.

In step S705, the object tracking unit 203 performs object trackingprocessing. That is, the object tracking unit 203 associates the objectdetected from the frame with an object detected from another frameaccording to a predetermined condition. For example, if the same objectis present in each of a plurality of frames, the object is associatedaccording to the object tracking processing.

In step S706, the locus management unit 207 updates locus informationaccording to a result of the tracking processing performed in step S705.The update of the locus information corresponds to addition of theinformation 303 illustrated in FIG. 3.

In step S707, the human body detection unit 204 uses the parameter setby the parameter setting unit 205 to perform human body detectionprocessing with respect to the object detected by the object detectionunit 202 and a region in the vicinity of such an object.

Herein, the human body detection processing performed by the controlapparatus 200 of the present exemplary embodiment is described in detailwith reference to a flowchart illustrated in FIG. 8.

In step S801, the parameter control unit 212 acquires a settingparameter (setting information such as a maximum size and a minimum sizefor human body detection) set by the parameter setting unit 205. Thesetting parameter is not limited to the information of the maximum sizeand the minimum size for human body detection. That is, in step S801,the parameter control unit 212 acquires a parameter for performing videoimage recognition processing. Moreover, the parameter control unit 212acquires information about a current zoom magnification. The controlapparatus 200 of the present exemplary embodiment is installed in thecamera, and the parameter control unit 212 acquires the informationabout the zoom magnification from a storage unit inside the camera.However, the parameter control unit 212 may acquire the informationabout the zoom magnification from the PC 104 connected to the camera.

In step S802, the parameter control unit 212 determines whether the zoommagnification is changed by the zoom control unit 211. That is, theparameter control unit 212 determines whether the information about thezoom magnification acquired last time differs from the information aboutthe zoom magnification acquired this time. If the parameter control unit212 determines that a change in the zoom magnification is detected (YESin step S802), the operation proceeds to step S803. On the other hand,if the parameter control unit 212 determines that a change in the zoommagnification is not detected (NO in step S802), the operation proceedsto step S804.

In step S803, the parameter control unit 212 determines a parameter tobe used in the human body detection processing in step S804 from theparameter acquired in step S801 and the zoom magnification acquired instep S801. For example, when the zoom magnification is changed from samesize to 2 times, the parameter control unit 212 determines that themaximum size for human body detection is to be changed to 2 times.However, this is a mere example. That is, the parameter control unit 212changes the parameter acquired in step S801 according to a change in thezoom magnification of the image capturing unit.

Further, the parameter control unit 212 of the present exemplaryembodiment transmits a notification to the display device 210. Thenotification includes a message indicating that the parameter of therecognition processing has been changed according to a change in thezoom magnification, and notifying a changed parameter. Consequently, thedisplay device 210 can display the message and the changed parameter(e.g., a rectangle corresponding to the maximum size or the minimum sizefor human body detection) on the parameter setting screen. Herein, themessage indicating that the parameter of the video image recognitionprocessing has been changed can be displayed.

In step S804, the human body detection unit 204 uses the parameterdetermined in step S803 (if the zoom magnification is not changed, aparameter according to the setting set by the user) to perform the humanbody detection processing. Upon completion of the human body detectionprocessing in step S804, the operation proceeds to step S708 of theflowchart illustrated in FIG. 7.

In step S708, the human body detection unit 204 determines whether ahuman body is detected in step S707. If the human body detection unit204 determines that the human body is detected (YES in step S708), theoperation proceeds to step S709. On the other hand, if the human bodydetection unit 204 determines that the human body is not detected (NO instep S708), the operation proceeds to step S711.

In step S709, the object association unit 206 associates the objectdetected in step S703 with the human body detected in step S707.Accordingly, the object association unit 206 associates the object withthe human body according to an overlap region between the circumscribedrectangle of the object and the circumscribed rectangle of the humanbody as described above.

In step S710, the locus management unit 207 updates locus informationbased on a result of the association processing performed in the stepS709. The update of the locus information corresponds to addition of theinformation 303 illustrated in FIG. 3. In step S711, the locusinformation determination unit 208 performs locus informationdetermination processing to determine whether the object has passed adetection line. The locus information determination unit 208 determineswhether the object has passed through the detection line. The locusinformation determination unit 208 determines the passage of the objectbased on whether a movement vector has intersected a line segment forthe passage detection. The movement vector indicates a movement from ahuman body attribute object in the immediate preceding frame of a targetframe to a human body attribute object in the target frame. The humanbody attribute object represents an object that is determined as anassociated object and provided with the same object ID by the objecttracking unit 203.

In step S712, the external output unit 209 outputs a processing resultregarding the video image recognition processing to an external unit.Then, the operation returns to step S712. For example, the externaloutput unit 209 outputs position information of the circumscribedrectangle to the display device 210 such that circumscribed rectanglesof a detected object and a detected human body are displayed on a screendisplaying a captured image. Further, for example, if passage of a humanthrough a detection line or intrusion into a detection region isdetected, the external output unit 209 outputs a detection result to thedisplay device 210 such that a message corresponding to the detectionresult is displayed on a display screen of the display device 210.

According to the present exemplary embodiment, therefore, a parameter ofvideo image recognition processing is changed according to a change inthe zoom magnification. Thus, the recognition processing can be moresuitably performed with respect to an image captured by an imagecapturing unit having a function of changing a zoom magnification. Theabove exemplary embodiment has been mainly described using the examplein which a maximum size and a minimum size for human body detectionserve as parameters. However, a detection target may be a predeterminedobject other than a human body, for example, a bicycle, a face of aperson, and an animal. If a bicycle is used as a detection target, amaximum size and a minimum size for bicycle detection are set asparameters for recognition processing. Such parameters can be changedaccording to a change in zoom magnification.

According to the above-described exemplary embodiment(s), therecognition processing is more suitably performed with respect to thevideo image captured by the image capturing unit having a function ofchanging the zoom magnification.

Other Embodiments

Additional embodiment(s) can also be realized by a computer of a systemor apparatus that reads out and executes computer executableinstructions (e.g., one or more programs) recorded on a storage medium(which may also be referred to more fully as a ‘non-transitorycomputer-readable storage medium’) to perform the functions of one ormore of the above-described embodiment(s) and/or that includes one ormore circuits (e.g., application specific integrated circuit (ASIC)) forperforming the functions of one or more of the above-describedembodiment(s), and by a method performed by the computer of the systemor apparatus by, for example, reading out and executing the computerexecutable instructions from the storage medium to perform the functionsof one or more of the above-described embodiment(s) and/or controllingthe one or more circuits to perform the functions of one or more of theabove-described embodiment(s). The computer may comprise one or moreprocessors (e.g., central processing unit (CPU), micro processing unit(MPU)) and may include a network of separate computers or separateprocessors to read out and execute the computer executable instructions.The computer executable instructions may be provided to the computer,for example, from a network or the storage medium. The storage mediummay include, for example, one or more of a hard disk, a random-accessmemory (RAM), a read only memory (ROM), a storage of distributedcomputing systems, an optical disk (such as a compact disc (CD), digitalversatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, amemory card, and the like.

While the present disclosure has been described with reference toexemplary embodiments, it is to be understood that these exemplaryembodiments are not seen to be limiting. The scope of the followingclaims is to be accorded the broadest interpretation so as to encompassall such modifications and equivalent structures and functions.

What is claimed is:
 1. A capturing apparatus comprising: a computerexecuting instructions that, when executed by the computer, cause thecomputer to function as: an acquisition unit configured to acquire afirst image captured at a first zoom magnification; a setting unitconfigured to set at least one of a position and a length of a segmentline in the first image for detecting an event which corresponds topassage of an object to be detected from the first image, according to auser instruction for specifying the segment line in a setting screen onwhich the first image is displayed; a control unit configured to changeat least one of the position and the length of the segment line set inthe first image, according to a change from the first zoom magnificationto a second zoom magnification different from the first zoommagnification; and a transmission unit configured to transmit, such thatthe segment line at least one of the position and the length of whichhas been changed by the control unit is displayed in the setting screenon which a second image captured at the second zoom magnification isdisplayed, information to an external apparatus after the control unithas changed at least one of the position and the length of the segmentline.
 2. The capturing apparatus according to claim 1, wherein thetransmission unit transmits, such that a detection result of detectingthe event is displayed, information to the external apparatus if theevent has been detected.
 3. The capturing apparatus according to claim1, further comprising a detection unit configured to detect the eventwhich corresponds to passage of the object through the segment line. 4.A control method for controlling a capturing apparatus, the controlmethod comprising: obtaining a first image captured at a first zoommagnification; setting at least one of a position and a length of asegment line in the first image for detecting an event which correspondsto passage of an object to be detected from the first image, accordingto a user instruction for specifying the segment line in a settingscreen on which the first image is displayed; changing at least one ofthe position and the length of the segment line set in the first image,according to a change from the first zoom magnification to a second zoommagnification different from the first zoom magnification; andtransmitting, such that the segment line at least one of the positionand the length of which has been changed in the changing is displayed inthe setting screen on which a second image captured at the second zoommagnification is displayed, information to an external apparatus afterat least one of the position and the length of the segment line has beenchanged in the changing.
 5. A non-transitory computer-readable storagemedium storing a program for causing a computer to perform operationsaccording to claim
 4. 6. The control method according to claim 4,wherein information is transmitted to the external apparatus in thetransmitting if the event has been detected, such that a detectionresult of detecting the event is displayed.
 7. The control methodaccording to claim 4, further comprising detecting the event whichcorresponds to passage of the object through the segment line.
 8. Acapturing apparatus comprising: a computer executing instructions that,when executed by the computer, cause the computer to function as: anacquisition unit configured to acquire a first image captured at a firstzoom magnification; a setting unit configured to set at least one of aposition and a size of a region in the first image for detecting anevent which corresponds to intrusion of an object to be detected fromthe first image, according to a user instruction for specifying theregion in a setting screen on which the first image is displayed; acontrol unit configured to change at least one of the position and thesize of the region set in the first image, according to a change fromthe first zoom magnification to a second zoom magnification differentfrom the first zoom magnification; and a transmission unit configured totransmit, such that the region at least one of the position and the sizeof which has been changed by the control unit is displayed in thesetting screen on which a second image captured at the second zoommagnification is displayed, information to an external apparatus afterthe control unit has changed at least one of the position and the sizeof the region.
 9. The capturing apparatus according to claim 8, whereinthe transmission unit transmits, such that a detection result ofdetecting the event is displayed, information to the external apparatusif the event has been detected.
 10. The capturing apparatus according toclaim 8, further comprising a detection unit configured to detect theevent which corresponds to intrusion of the object into the region. 11.A control method for controlling a capturing apparatus,the controlmethod comprising: obtaining a first image captured at a first zoommagnification; setting at least one of a position and a size of a regionin the first image for detecting an event which corresponds to intrusionof an object to be detected from the first image, according to a userinstruction for specifying the region in a setting screen on which thefirst image is displayed; changing at least one of the position and thesize of the region set in the first image, according to a change fromthe first zoom magnification to a second zoom magnification differentfrom the first zoom magnification; and transmitting, such that theregion at least one of the position and the size of which has beenchanged in the changing is displayed in the setting screen on which asecond image captured at the second zoom magnification is displayed,information to an external apparatus after at least one of the positionand the size of the region has been changed in the changing.
 12. Thecontrol method according to claim 11, wherein information is transmittedto the external apparatus in the transmitting if the event has beendetected, such that a detection result of detecting the event isdisplayed.
 13. The control method according to claim 11, furthercomprising detecting the event which corresponds to intrusion of theobject into the region.
 14. A non-transitory computer-readable storagemedium storing a program for causing a computer to perform operationsaccording to claim 11.